## Abstract and Applied Analysis

### Regularized Least Square Regression with Unbounded and Dependent Sampling

#### Abstract

This paper mainly focuses on the least square regression problem for the $\alpha$-mixing and $\varphi$-mixing processes. The standard bound assumption for output data is abandoned and the learning algorithm is implemented with samples drawn from dependent sampling process with a more general output data condition. Capacity independent error bounds and learning rates are deduced by means of the integral operator technique.

#### Article information

Source
Abstr. Appl. Anal., Volume 2013 (2013), Article ID 139318, 7 pages.

Dates
First available in Project Euclid: 27 February 2014

https://projecteuclid.org/euclid.aaa/1393511839

Digital Object Identifier
doi:10.1155/2013/139318

Mathematical Reviews number (MathSciNet)
MR3044987

Zentralblatt MATH identifier
1273.62208

#### Citation

Chu, Xiaorong; Sun, Hongwei. Regularized Least Square Regression with Unbounded and Dependent Sampling. Abstr. Appl. Anal. 2013 (2013), Article ID 139318, 7 pages. doi:10.1155/2013/139318. https://projecteuclid.org/euclid.aaa/1393511839